Life Sciences Commons^™

Inverse Probability Weighting In Survival Analysis And Network Analysis, Yukun Lu

Doctoral Dissertations

Inverse probability weighting is a popular technique to accommodate selection bias due to non-random sampling and missing data. In the first chapter, we develop an inverse probability weighted estimator and an augmented inverse probability weighted estimator of regression coefficients for a linear model with randomly censored covariates, when the censoring mechanism may be dependent on the outcome. We investigate the asymptotic properties of both estimators and evaluate their finite sample performance through extensive simulation studies. We apply the proposed methods to an Alzheimer’s disease study. In the second chapter, we present an application of network analysis in a study of …

Applications Of Statistical Physics To Ecology: Ising Models And Two-Cycle Coupled Oscillators, Vahini Reddy Nareddy

Doctoral Dissertations

Many ecological systems exhibit noisy period-2 oscillations and, when they are spatially extended, they undergo phase transition from synchrony to incoherence in the Ising universality class. Period-2 cycles have two possible phases of oscillations and can be represented as two states in the bistable systems. Understanding the dynamics of ecological systems by representing their oscillations as bistable states and developing dynamical models using the tools from statistical physics to predict their future states is the focus of this thesis. As the ecological oscillators with two-cycle behavior undergo phase transitions in the Ising universality class, many features of synchrony and equilibrium …

Statistical Improvements For Ecological Learning About Spatial Processes, Gaetan L. Dupont

Masters Theses

Ecological inquiry is rooted fundamentally in understanding population abundance, both to develop theory and improve conservation outcomes. Despite this importance, estimating abundance is difficult due to the imperfect detection of individuals in a sample population. Further, accounting for space can provide more biologically realistic inference, shifting the focus from abundance to density and encouraging the exploration of spatial processes. To address these challenges, Spatial Capture-Recapture (“SCR”) has emerged as the most prominent method for estimating density reliably. The SCR model is conceptually straightforward: it combines a spatial model of detection with a point process model of the spatial distribution of …

Monitoring Mammals At Multiple Scales: Case Studies From Carnivore Communities, Kadambari Devarajan

Doctoral Dissertations

Carnivores are distributed widely and threatened by habitat loss, poaching, climate change, and disease. They are considered integral to ecosystem function through their direct and indirect interactions with species at different trophic levels. Given the importance of carnivores, it is of high conservation priority to understand the processes driving carnivore assemblages in different systems. It is thus essential to determine the abiotic and biotic drivers of carnivore community composition at different spatial scales and address the following questions: (i) What factors influence carnivore community composition and diversity? (ii) How do the factors influencing carnivore communities vary across spatial and temporal …

Interacting Effects Of Climate And Biotic Factors On Mesocarnivore Distribution And Snowshoe Hare Demography Along The Boreal-Temperate Ecotone, Alexej P. Siren

Doctoral Dissertations

The motivation of my dissertation research was to understand the influence of climate and biotic factors on range limits with a focus on winter-adapted species, including the Canada lynx (Lynx canadensis), American marten (Martes americana), and snowshoe hare (Lepus americanus). I investigated range dynamics along the boreal-temperate ecotone of the northeastern US. Through an integrative literature review, I developed a theoretical framework building from existing thinking on range limits and ecological theory. I used this theory for my second chapter to evaluate direct and indirect causes of carnivore range limits in the northeastern US, …

Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh

Doctoral Dissertations

Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to designing …

Population Viability And Connectivity Of The Federally Threatened Eastern Indigo Snake In Central Peninsular Florida, Javan Bauder

Doctoral Dissertations

Understanding the factors influencing the likelihood of persistence of real-world populations requires both an accurate understanding of the traits and behaviors of individuals within those populations (e.g., movement, habitat selection, survival, fecundity, dispersal) but also an understanding of how those traits and behaviors are influenced by landscape features. The federally threatened eastern indigo snake (EIS, Drymarchon couperi) has declined throughout its range primarily due to anthropogenically-induced habitat loss and fragmentation making spatially-explicit assessments of population viability and connectivity essential for understanding its current status and directing future conservation efforts. The primary goal of my dissertation was to understand how …

Real-Time Dengue Forecasting In Thailand: A Comparison Of Penalized Regression Approaches Using Internet Search Data, Caroline Kusiak

Masters Theses

Dengue fever affects over 390 million people annually worldwide and is of particu- lar concern in Southeast Asia where it is one of the leading causes of hospitalization. Modeling trends in dengue occurrence can provide valuable information to Public Health officials, however many challenges arise depending on the data available. In Thailand, reporting of dengue cases is often delayed by more than 6 weeks, and a small fraction of cases may not be reported until over 11 months after they occurred. This study shows that incorporating data on Google Search trends can improve dis- ease predictions in settings with severely …

Modelling Bird Migration With Motus Data And Bayesian State-Space Models, Justin Baldwin

Masters Theses

Bird migration is a poorly-known yet important phenomenon, as understanding movement patterns of birds can inform conservation strategies and public health policy for animal-borne diseases. Recent advances in wildlife tracking technology, in particular the Motus system, have allowed researchers to track even small flying birds and insects with radio transmitters that weigh fractions of a gram. This system relies on a community-based distributed sensor network that detects tagged animals as they move through the detection nodes on journeys that range from small local movements to intercontinental migrations. The quantity of data generated by the Motus system is unprecedented, is on …

Multiple Testing Correction With Repeated Correlated Outcomes: Applications To Epigenetics, Katie Leap

Masters Theses

Epigenetic changes (specifically DNA methylation) have been associated with adverse health outcomes; however, unlike genetic markers that are fixed over the lifetime of an individual, methylation can change. Given that there are a large number of methylation sites, measuring them repeatedly introduces multiple testing problems beyond those that exist in a static genetic context. Using simulations of epigenetic data, we considered different methods of controlling the false discovery rate. We considered several underlying associations between an exposure and methylation over time.

We found that testing each site with a linear mixed effects model and then controlling the false discovery rate …

Statistical Methods For High Dimensional Data Arising From Large Epidemiological Studies, Hui Xu

Doctoral Dissertations

In this thesis, we propose statistical models for addressing commonly encountered data types and study designs in large epidemiologic investigations aimed at understanding the molecular basis of complex disorders. The motivating applications come from diverse disease areas in Women's Health, including the study of type II diabetes in the Women's Health Initiative (WHI), invasive breast cancer in the Nurses' Health Study and the study of the metabolomic underpinnings of cardiovascular disease in the WHI. We have also put significant effort into making the implementation of the proposed methods accessible through freely available, user-friendly software packages in R. The first chapter …

Estimation Problems In Complex Field Studies With Deep Interactions: Time-To-Event And Local Regression Models For Environmental Effects On Vital Rates, Krzysztof M. Sakrejda

Doctoral Dissertations

Field studies that measure vital rates in context over extended time periods are a cornerstone of our understanding of population processes. These studies inform us about the relationship between biological process and environmental noise in an irreplaceable way. These data sets bring ``big data'' and ``big model'' challenges, which limit the application of standard software (e.g., \textbf{BUGS}). The environmental sensitivity of vital rates is also expected to exhibit interactions and non-linearity, which typically result in difficult model selection questions in large data sets. Finally, long-term ecological data sets often contain complex temporal structure. In commonly applied discrete-time models complex temporal …

Evaluating Predictors Of An Individual’S Dietary Intake Latent Value Under Different Mixed Models, Shuli Yu

Doctoral Dissertations

The accurate estimation of an individual’s usual dietary intake is important since the estimates are essential to uncover the diet-disease relationships. This study explores a more accurate method to estimate an individual’s latent value of usual dietary intake when it is repeatedly measured using a 24-hour dietary recall (24HR) and seven day dietary recall (7DDR), accounting for random measurement error and bias. The performance of the (empirical) predictor of subject’s latent value obtained under the finite population mixed model (FPMM) framework is compared with those obtained under the usual mixed model and the measurement error model through a simulation study. …